Error in Maxent maps
Dear Irene, Since your background points are not real occurrences (so you do not know the prevalence of the species), and MaxEnt is a presence-only method, the predicted value can not directly treated as probability of occurrence. Also you should never compare the raw predicted values between species (or between different models), even if you use presence-absence data/method. 0.005 for Species1 is not better/worse than 0.95 for Species2. So I would say that the predicted values are OK. If you really want to compare predictions between species, I recommend you to rescale the raw values to a 5-level ordinal scale using specific thresholds that account for observed presences. Please refer to Somodi et al. (2017): https://www.researchgate.net/publication/318561746_Implementation_and_application_of_multiple_potential_natural_vegetation_models_-_a_case_study_of_Hungary Have a nice week, ?kos Bede-Fazekas Hungarian Academy of Sciences 2021.01.12. 13:47 keltez?ssel, Irene Rojo ?rta:
Dear all, My name is Irene and I am performing Maxent SDM in R with the dismo package. I am working with several species, performing one analysis for each species, and all are working fine, i.e. the models have sense, except two of them. For those species, I can run Maxent models and I get a very high value of AUC (0.99) but the resulting maps show values between 0 and 0.005, when for the rest of the species they are between 0 and (almost) 1. So maps have no sense. The predictor variables are the same, and those two species are not the ones with the lowest number of occurrences (this is the first reason I thought that could be affecting the results). I know it is not easy to know what is going on, but I am doing exactly the same with all species. If anyone can guess the error or know which part of the analysis is more sensitive so I can check it again I would be very grateful. Thanks a lot in advance, Irene [[alternative HTML version deleted]]
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